• Advise and influence program directors, factory leaders, and external customers while leveraging strong communication, influence management, and presentation skills to effectively interact with stakeholders. • Manage and execute the processes, standards and plans in support of the Operations, Supply Chain and Quality (OSC) strategy. • Be accountable to lead tooling procurement across the Portfolio implementing synergies cost savings and strategic planning in excess of $20M. • Provide Cost Account Management (CAM) support as needed. • Engage and support metrics for monthly Management Board Review meetings. • Provide support for proposals including writing Basis of Estimates (BOEs) and Standard Bidding Tool (SBT). • Provide support as needed for Visual Factory including programming understanding of dashboard Program BI. • Provide support to the Material Program Manager (MPM) team for metrics, data analytics, presentations and supplier engagements. • Implement key performance indicators internally with Operations to ensure timely delivery to customers and adherence to the plan. • Lead initiatives focused on driving operational excellence, continuous improvement, and efficiency across OSC processes (CORE).

• Work with the AI/ML team to develop and apply novel machine learning frameworks and methodologies supporting the design and evaluation of turbine components for the Hot Section Engineering organization • Deploy AI/ML applications and/or agentic workflows within Hot Section processes and tools • Communicate technical solutions and insights to internal/external customers and organization leadership • Advocate for and participate in fundamental AI/ML research with academic and external research institute partners • Collaborate with RTX AI/ML teams to strengthen corporate level AI/ML initiatives and infrastructure

• Build and maintain dbt models that transform source data into clean, tested datasets for analytics and reporting. • Write SQL to investigate data issues, validate new sources, and answer stakeholder questions with accurate, reproducible logic. • Implement data quality checks (dbt tests, freshness, reconciliations) and help resolve production data issues, including on-call rotation. • Document models, metrics, and lineage so teammates and stakeholders understand definitions and dependencies. • Partner with analysts and business teams to deliver production-ready data products—not just ad hoc queries. • Use modern tooling—including AI-assisted frameworks—to move faster while keeping quality and review standards high.

• Business Intelligence Strategy: Translate the client's business objectives into effective information management and data intelligence strategies. • Pipeline Engineering (ETL): Organize, collect, transform and process large volumes of data from diverse sources, ensuring the maintenance and evolution of robust pipelines. • Data Visualization Culture: Lead the creation, modeling and presentation of metrics through analytical panels and intelligent dashboards using Amazon QuickSight, ensuring leadership makes decisions based on reliable data. • Security and Governance: Ensure control, integrity, quality and maximum security in access to the data handled. • Squad Collaboration: Actively participate in business refinement and technical development phases, working as part of a team within a continuous delivery culture.